In a contact centers, it has become more common to store recordings of contact center communication sessions for later review and analysis, e.g. for performance evaluation or training purposes. In order to facilitate easier searching and classification of these recordings, many systems provide the ability to tag the recordings with appropriate metadata, which can then be subsequently used to search and analyze the call recordings. Typically this metadata consists of static pieces of data regarding the communication session, such as Automatic Number Identification (ANI), contact center agent skill set, Call ID etc., which do not vary during the call.
The phonetic search technology provided by Nexidia Inc. (www.nexidia.com) is operable to monitor audio for recognition of specific query criteria, and can associate specific predefined tags with the media stream using time indexing (e.g. tax X occurs at 3 minutes and 25 seconds into the stream). The Nexidia system is also operable to create an index of phonemes and where they occur in an audio stream, which can aid in the location of the discussion of topics in a media recording.
U.S. patent application Ser. No. 12/249,451 filed on Oct. 10, 2008, now U.S. Pat. No. 8,301,447, which issued on Oct. 30, 2012 (which is commonly assigned), describes a system which is operable to time index which party is speaking in a media stream involving two or more parties (such as indexing when an agent or a customer is speaking in a contact centre) or who is speaking throughout a multiparty conference call. This makes it possible to subsequently determine the flow of conversation during a media stream, and it can also be used to see if there is ever an occasion when one party may speak over another party (this would be important in a contact centre environment, if for example an agent speaks over a customer, this may be an indication of bad contact centre practice). However, there is a need for an improved system for analyzing a recording of a contact center communication session, which allows for better analysis of the session characteristics.